Research output per year
Research output per year
Personal profile
In Korean
말리페디 람모한 교수(IT대학 전자공학부)
Education
o (2005) B.Tech., Acharya Nagarjuna University, India
o (2007) M.Sc., Nanyang Technological University, Singapore
o (2010) Ph.D., nanyang Technological University, Singapore
o (2007) M.Sc., Nanyang Technological University, Singapore
o (2010) Ph.D., nanyang Technological University, Singapore
Professional Experience
o (2012~Present) Assistant/Associate Professor/Full Professor, Kyungpook National University, Daegu
o (2011~2012) Research Fellow, Kyungpook National University, Daegu
o (2011~2011) Research Fellow, Nanyang Technological University, Singapore
o (2010~2011) Research Associate, Nanyang Technological University, Singapore
o (2008~2009) Research Associate, Nanyang Technological University, Singapore
o (2007~2008) Project Officer, Nanyang Technological University, Singapore
o (2011~2012) Research Fellow, Kyungpook National University, Daegu
o (2011~2011) Research Fellow, Nanyang Technological University, Singapore
o (2010~2011) Research Associate, Nanyang Technological University, Singapore
o (2008~2009) Research Associate, Nanyang Technological University, Singapore
o (2007~2008) Project Officer, Nanyang Technological University, Singapore
Research Interests
Computer vision and tracking
Application-specific algorithm design and optimization for machine learning
Development/improvement of evolutionary algorithms for solving single/multi-objective,
constrained/unconstrained optimization problems
Smart Home - Non-intrusive load monitoring (NILM), Device Scheduling and Energy
Management
Smart Grid – Generation scheduling, planning and incentive design
Smart City – Machine learning for smart city applications such as safety monitoring,
disaster management.
Application-specific algorithm design and optimization for machine learning
Development/improvement of evolutionary algorithms for solving single/multi-objective,
constrained/unconstrained optimization problems
Smart Home - Non-intrusive load monitoring (NILM), Device Scheduling and Energy
Management
Smart Grid – Generation scheduling, planning and incentive design
Smart City – Machine learning for smart city applications such as safety monitoring,
disaster management.
Major Research Achievements
o Prediction-guided multi-objective reinforcement learning with corner solution search
o Covariance matrix adaptation evolution strategy based on ensemble of mutations for parking navigation and maneuver of autonomous vehicles
o Predicting early mycotoxin contamination in stored wheat using machine learning
o Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities
o Covariance matrix adaptation evolution strategy based on ensemble of mutations for parking navigation and maneuver of autonomous vehicles
o Predicting early mycotoxin contamination in stored wheat using machine learning
o Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities
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Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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A study on challenges and solutions in artificial intelligence-driven demand side optimization and security enhancement for smart grids
Yerra, C., Teeparthi, K., Ramavathu, S. N., Rao, S. N. V. B., Kumar, Y. V. P. & Mallipeddi, R., Jan 2026, In: Computers and Electrical Engineering. 129, 110779.Research output: Contribution to journal › Article › peer-review
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TransE2UNet: Edge Guided TransEfficientUNET for Generalized Colon Polyp Segmentation from Endoscopy Images
Kar, S., Mukhopadhyay, S., Kundu, S., Jha, D. & Mallipeddi, R., 2026, Medical Image Understanding and Analysis - 29th Annual Conference, MIUA 2025, Proceedings. Ali, S., Hogg, D. C. & Peckham, M. (eds.). Springer Science and Business Media Deutschland GmbH, p. 3-16 14 p. (Lecture Notes in Computer Science; vol. 15918 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Visual Recognition of Crop Composite Planting Based on Vision Transformer
Guo, Z., Yu, X., Wang, S. & Rammohan, M., 2026, Intelligent Systems - Proceedings of 5th International Conference on Machine Learning, IoT and Big Data, ICMIB 2025. Udgata, S. K., Mohapatra, D., Sethi, S. & Rana, M. E. (eds.). Springer Science and Business Media Deutschland GmbH, p. 296-306 11 p. (Lecture Notes in Networks and Systems; vol. 1623 LNNS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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A fitness-assignment method for evolutionary constrained multi-objective optimization
Ajani, O. S., M., S. S. R., Paul, A. & Mallipeddi, R., Dec 2025, In: Computers and Electrical Engineering. 128, 110769.Research output: Contribution to journal › Article › peer-review
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A multi-objective benchmark for UAV path planning with baseline results
Darlan, D., Ajani, O. S., Paul, A. & Mallipeddi, R., Jul 2025, In: Swarm and Evolutionary Computation. 96, 101968.Research output: Contribution to journal › Article › peer-review